Martin Ma.

Engineering × Data × AI

Building data-driven solutions for real-world problems.

I'm an engineer passionate about using data, software, and AI to solve real-world problems.

With a background in materials science and industrial engineering, I focus on turning complex operational challenges into efficient, data-driven solutions.

I'm currently building tools to analyze manufacturing performance, identify bottlenecks, and support smarter decisions. My goal is to bridge engineering, data science, and AI to make complex systems more intelligent, efficient, and adaptable.

Explore my work
01SELECTED WORK

Slitting Barcode Assistant

Why I built it

I saw how repeated calculations and changing production plans created extra coordination between teams. Each change meant more information to check and communicate, making routine preparation harder to keep consistent.

I built this program around one concrete part of that workflow: preparing slitting data. It brings production calculations, master-roll checks, and barcode validation into one place, then exports an Excel file for manual MES upload. My aim was to make that preparation easier to review and repeat.

View Case Study V1 Prototype
Slitting Barcode Assistant showing production inputs and the calculated plan for an example batch
Actual application · production planning with example dataClick image to enlarge
02SELECTED WORK

AI Work Order Automation

A production automation system designed to calculate demand, allocate machines, match master rolls, generate barcodes, and create MES-ready output.

View Case Study In Development
PRODUCTION WORKFLOW
  1. 01Work OrderINPUT
  2. 02Demand CalculationCALCULATE
  3. 03Machine AllocationALLOCATE
  4. 04Master Roll MatchingMATCH
  5. 05Barcode GenerationGENERATE
  6. 06MES OutputEXPORT
Conceptual system diagram · in development
03SELECTED WORK

Slitting Capacity Improvement

Engineering Leadership & Process Optimization

I led a slitting improvement project at GNEM, combining firsthand observation and analysis of production records with changes to preparation, inspection, and shared support.

View Case Study Engineering Case Study
Production capacity
8 16good cuts per machine / 12-hour shift

16 is normalized: 32 measured daily cuts ÷ 2 shifts.

Normal production CTBefore → after
47.5 35 min

Normal CT uses a matched test and excludes abnormal downtime.